Applying Machine Learning NLP Algorithm for Reconciliation Geology and Petrophysics in Rock Typing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3ASNFA2W2U" target="_blank" >RIV/00216208:11320/23:SNFA2W2U - isvavai.cz</a>
Result on the web
<a href="https://onepetro.org/SPEADIP/proceedings-abstract/23ADIP/2-23ADIP/534415" target="_blank" >https://onepetro.org/SPEADIP/proceedings-abstract/23ADIP/2-23ADIP/534415</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2118/216223-MS" target="_blank" >10.2118/216223-MS</a>
Alternative languages
Result language
angličtina
Original language name
Applying Machine Learning NLP Algorithm for Reconciliation Geology and Petrophysics in Rock Typing
Original language description
"Applying text analysis, a crucial area in natural language processing, aims to extract meaningful insights and valuable information from unstructured textual data. With the vast amount of text generated every day, automated and efficient text analysis methods are becoming increasingly essential. Machine learning techniques have revolutionized the analysis and understanding of text data. In this paper, we present a comprehensive summary of the available methods for text analysis using machine learning, covering various stages of the process, from data preprocessing to advanced text modeling approaches. The overview explores the strengths and limitations of each method, providing researchers and practitioners with valuable insights for their text analysis endeavors."
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
"Abu Dhabi International Petroleum Exhibition and Conference"
ISBN
978-1-959025-07-8
ISSN
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e-ISSN
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Number of pages
1
Pages from-to
D021S054R001
Publisher name
SPE
Place of publication
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Event location
Koper, Slovenia
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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